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Transcript analysis of laser capture microdissected white matter astrocytes and higher phenol sulfotransferase 1A1 expression during autoimmune neuroinflammation

Overview of attention for article published in Journal of Neuroinflammation, July 2015
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Title
Transcript analysis of laser capture microdissected white matter astrocytes and higher phenol sulfotransferase 1A1 expression during autoimmune neuroinflammation
Published in
Journal of Neuroinflammation, July 2015
DOI 10.1186/s12974-015-0348-y
Pubmed ID
Authors

Flora Guillot, Alexandra Garcia, Marion Salou, Sophie Brouard, David A. Laplaud, Arnaud B. Nicot

Abstract

Astrocytes, the most abundant cell population in mammal central nervous system (CNS), contribute to a variety of functions including homeostasis, metabolism, synapse formation, and myelin maintenance. White matter (WM) reactive astrocytes are important players in amplifying autoimmune demyelination and may exhibit different changes in transcriptome profiles and cell function in a disease-context dependent manner. However, their transcriptomic profile has not yet been defined because they are difficult to purify, compared to gray matter astrocytes. Here, we isolated WM astrocytes by laser capture microdissection (LCM) in a murine model of multiple sclerosis to better define their molecular profile focusing on selected genes related to inflammation. Based on previous data indicating anti-inflammatory effects of estrogen only at high nanomolar doses, we also examined mRNA expression for enzymes involved in steroid inactivation. Experimental autoimmune encephalomyelitis (EAE) was induced in female C57BL6 mice with MOG35-55 immunization. Fluorescence activated cell sorting (FACS) analysis of a portion of individual spinal cords at peak disease was used to assess the composition of immune cell infiltrates. Using custom Taqman low-density-array (TLDA), we analyzed mRNA expression of 40 selected genes from immuno-labeled laser-microdissected WM astrocytes from lumbar spinal cord sections of EAE and control mice. Immunohistochemistry and double immunofluorescence on control and EAE mouse spinal cord sections were used to confirm protein expression in astrocytes. The spinal cords of EAE mice were infiltrated mostly by effector/memory T CD4+ cells and macrophages. TLDA-based profiling of LCM-astrocytes identified EAE-induced gene expression of cytokines and chemokines as well as inflammatory mediators recently described in gray matter reactive astrocytes in other murine CNS disease models. Strikingly, SULT1A1, but not other members of the sulfotransferase family, was expressed in WM spinal cord astrocytes. Moreover, its expression was further increased in EAE. Immunohistochemistry on spinal cord tissues confirmed preferential expression of this enzyme in WM astrocytic processes but not in gray matter astrocytes. We described here for the first time the mRNA expression of several genes in WM astrocytes in a mouse model of multiple sclerosis. Besides expected pro-inflammatory chemokines and specific inflammatory mediators increased during EAE, we evidenced relative high astrocytic expression of the cytoplasmic enzyme SULT1A1. As the sulfonation activity of SULT1A1 inactivates estradiol among other phenolic substrates, its high astrocytic expression may account for the relative resistance of this cell population to the anti-neuroinflammatory effects of estradiol. Blocking the activity of this enzyme during neuroinflammation may thus help the injured CNS to maintain the anti-inflammatory activity of endogenous estrogens or limit the dose of estrogen co-regimens for therapeutical purposes.

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 19%
Student > Master 6 16%
Student > Bachelor 5 14%
Professor > Associate Professor 4 11%
Student > Doctoral Student 3 8%
Other 6 16%
Unknown 6 16%
Readers by discipline Count As %
Neuroscience 12 32%
Biochemistry, Genetics and Molecular Biology 4 11%
Agricultural and Biological Sciences 4 11%
Medicine and Dentistry 4 11%
Veterinary Science and Veterinary Medicine 2 5%
Other 3 8%
Unknown 8 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 May 2016.
All research outputs
#15,339,713
of 22,816,807 outputs
Outputs from Journal of Neuroinflammation
#1,748
of 2,629 outputs
Outputs of similar age
#153,651
of 262,801 outputs
Outputs of similar age from Journal of Neuroinflammation
#29
of 47 outputs
Altmetric has tracked 22,816,807 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,629 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 262,801 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.